Low-carbon optimization scheduling method for energy gradient utilization of virtual power plant considering organic Rankine cycle

Abstract

The invention discloses a low-carbon optimal scheduling method for energy gradient utilization of a virtual power plant considering an organic Rankine cycle, and belongs to the field of low-carbon economic scheduling. The method comprises the following steps: establishing a virtual power plant architecture considering the organic Rankine cycle; based on a virtual power plant framework of an organic Rankine cycle, after the # imgabs0 # efficiency of heat energy utilization is considered, an organic Rankine cycle output model utilizing waste heat to generate power is established; establishing a power-to-gas operation model; an organic Rankine cycle output model and a power-to-gas operation model are combined, and a combined heat and power unit output model containing a power-to-gas and organic Rankine cycle device is established; establishing a stepped carbon transaction model under a carbon quota mechanism; establishing a comprehensive demand response model; and solving the minimum comprehensive operation cost of the virtual power plant. According to the method, the virtual power plant is optimized according to the comprehensive demand response, the flexible and low-carbon operation potential of the load side in the virtual power plant is mined, wind power consumption is promoted, the energy purchase cost and the wind curtailment cost of the virtual power plant are reduced, and the method has positive influence on carbon emission reduction of the virtual power plant.

Description

Technical Field

[0001] The present invention relates to a low-carbon optimization dispatching method for cascade utilization of energy in a virtual power plant taking into account an organic Rankine cycle, and belongs to the field of low-carbon economic dispatching. Background Art

[0002] In the context of the increasing proportion of new energy, the problems of low energy utilization and insufficient low carbon are becoming increasingly serious. Due to the uncertainty and volatility of new energy output and the opposite characteristics of the safety and stability requirements of the power system, new energy cannot currently undertake the task of load power supply alone. At the same time, due to the existence of thermal load and gas load, traditional carbon-containing power sources mainly in the form of gas are still needed for energy supply. However, at present, the energy utilization rate of cogeneration units in my country is not high, the gas-to-electricity efficiency is only about 20-30%, the gas-to-heat efficiency is about 70%, and the comprehensive utilization rate of natural gas combustion is only about 50%. The low energy utilization efficiency has caused many resource wastes; however, the control of carbon dioxide produced after burning natural gas is also an urgent problem that the current power system needs to solve.

[0003] Due to the forward development of society and economy, my country's demand for energy has increased instead of decreased, and the contradiction between the demand for carbon reduction and the increasing carbon emissions during energy use has become increasingly prominent. Increasing the acceptance of new energy and balancing the supply and demand relationship by calling on flexible resources such as the power supply side, load side, and energy storage side of the power system has become an important means to achieve green and low-carbon development. However, the geographical location of new energy, load and other resources is relatively scattered and volatile. The two-way uncertainty increases the complexity of the power system and the difficulty of aggregating flexible resources. The use of advanced communication technology to effectively aggregate relatively scattered resources such as source, load, network and storage sides and participate in the low-carbon dispatch of the power system to achieve the green development of the power system. Virtual Power Plant (VPP) will play an increasingly important role in the future.

[0004] The application of VPP includes emission reduction, energy conservation, resource aggregation, etc. In terms of resource aggregation, Shenzhen has started the construction of VPP, and the amount of resource aggregation has begun to take shape, providing practical support for the subsequent realization of low-carbon, efficient and economic operation. In terms of VPP energy conservation and emission reduction, and economic scheduling, most of the current research uses strategies such as electricity-carbon coupling and gaming to achieve low-carbon scheduling, without considering the potential of energy efficiency to guide VPP carbon reduction; in terms of energy efficiency (i.e. In terms of efficiency, the organic Rankine cycle is one of my country's mature means of energy cascade utilization. The organic Rankine cycle waste heat power generation technology can be used to utilize the waste heat of the cogeneration unit to generate electricity and then supply the electrical load, decoupling the traditional cogeneration unit's "heat-to-electricity" supply mode. However, the method of using ORC power generation to directly supply the load does not conduct an in-depth analysis of the coupling degree between energy utilization efficiency and VPP's carbon reduction operation. The correlation between energy utilization efficiency and carbon trading is not high, and it is impossible to fully release the guiding potential of carbon trading on VPP carbon reduction. To improve the low-carbon and economic operation of VPP, how to achieve VPP The positive correlation coupling between efficiency and low-carbon scheduling is an issue that needs to be addressed.

[0005] In view of this, the present invention is proposed. Summary of the invention

[0006] The present invention provides a low-carbon optimization scheduling method for cascade utilization of energy in a virtual power plant considering an organic Rankine cycle, which is used to establish a low-carbon economic scheduling model for a virtual power plant and solve it to obtain an optimized operation plan for the virtual power plant.

[0007] The technical solution of the present invention is:

[0008] A low-carbon optimization scheduling method for cascade utilization of energy in a virtual power plant considering an organic Rankine cycle, comprising: step S1, establishing a virtual power plant architecture considering an organic Rankine cycle; the virtual power plant architecture considering an organic Rankine cycle comprises a power supply side, a load side, and an energy storage side, the power supply side comprises wind power and a combined heat and power unit, and the combined heat and power unit combines an organic Rankine cycle, a power-to-gas unit, a gas turbine, and a waste heat boiler, the load side comprises three types of loads: electricity, heat, and gas, and the energy storage side comprises three types of energy storage devices: electricity, heat, and gas; step S2, a virtual power plant architecture based on an organic Rankine cycle, in which thermal energy utilization is considered After calculating the efficiency, an organic Rankine cycle output model for power generation using waste heat is established; a power-to-gas operation model is established; the organic Rankine cycle output model and the power-to-gas operation model are combined to establish an output model of a combined heat and power unit including power-to-gas and organic Rankine cycle devices; step S3, under the carbon quota mechanism, a step-by-step carbon trading model is established; step S4, a comprehensive demand response model is established; step S5, based on the step-by-step carbon trading model and the comprehensive demand response model, an objective function and constraints for minimizing the comprehensive operating cost of a virtual power plant considering an organic Rankine cycle are established; based on the objective function and constraints for minimizing the comprehensive operating cost of a virtual power plant considering an organic Rankine cycle, a low-carbon optimal scheduling of energy cascade utilization of a virtual power plant considering an organic Rankine cycle is achieved.

[0009] As a further solution of the present invention, the output model of the combined heat and power unit containing the power-to-gas and organic Rankine cycle device is expressed as follows:

[0010]

[0011] P P2G,g (t) = η P2G P P2G,e (t);

[0012] P P2G,e (t) = P ORC,e (t)+P a,w (t);

[0013]

[0014] Where P ORC,h (t), P WHB,h (t) are the heat power of the organic Rankine cycle and the heat power entering the waste heat boiler during period t; P ORC,e (t) is the electric power generated by the organic Rankine cycle during period t; η ORC is the organic Rankine cycle thermoelectric conversion efficiency; P h,WHB (t) is the heating power of the waste heat boiler during period t; η WHB is the heat loss efficiency; P e,GT (t), P h,GT (t) are the electrical power and thermal power generated by the gas turbine during period t; P g,GT (t) is the natural gas power required by the gas turbine during period t; η e , η h,GT are the gas-to-electricity and gas-to-heat conversion efficiencies of the gas turbine during period t, respectively; are the upper and lower limits of GT gas power respectively; P h,GB (t) is the thermal power generated by the gas boiler during period t, P g,GB (t) is the gas power required by the gas boiler during period t; η GB is the heat conversion efficiency of the gas boiler; are the upper and lower limits of gas power of gas boiler respectively; P P2G,g (t) is the natural gas power output of the power-to-gas device during period t; η P2G is the conversion efficiency of the power-to-gas device; P P2G,e (t) is the electric power required by the power-to-gas device during period t; P a,w (t) is the wind power abandoned during period t; is the greenhouse gas mass of synthetic natural gas during period t; For transformation efficiency.

[0015] As a further scheme of the present invention, step S3 includes: obtaining the carbon quota of the virtual power plant based on the carbon quota model of the virtual power plant; obtaining the actual carbon emissions of the virtual power plant based on the actual carbon emission model of the virtual power plant; obtaining the carbon emissions of the virtual power plant participating in carbon trading based on the carbon quota of the virtual power plant and the actual carbon emissions of the virtual power plant; and establishing a stepped carbon trading model based on the carbon emissions of the virtual power plant participating in carbon trading to obtain the carbon trading cost.

[0016] As a further solution of the present invention, the actual carbon emission model of the virtual power plant is:

[0017] D VPP,a =D e,buy,a +D g,load,a +D IE,a -D P2G,a ;

[0018] Where D VPP,a , D e,buy,a , D g,load,a are the actual carbon emissions of virtual power plants, purchased electricity, and gas loads, respectively. IE,a is the sum of the actual carbon emissions of gas turbines and gas boilers, D P2G,a Carbon emissions absorbed by the power-to-gas device.

[0019] As a further solution of the present invention, the step-by-step carbon trading model is:

[0020]

[0021] D a =D VPP,a -D VPP ;

[0022] In the formula, is the carbon trading cost; λ is the carbon trading base price; D a is the carbon emissions of the virtual power plant participating in carbon trading; L is the length of the carbon emission interval; α is the price increase; D VPP,a is the actual carbon emission of the virtual power plant; D VPP Carbon quota for virtual power plants.

[0023] As a further solution of the present invention, step S5 includes:

[0024] Taking power balance constraint as constraint condition and minimizing comprehensive operation cost as goal for optimization, the low-carbon economic dispatch model of virtual power plant considering organic Rankine cycle is constructed as follows:

[0025] minF=min(f buy +f AD +f CO2 +f IDR );

[0026]

[0027] Where F is the total cost of the virtual power plant; buy 、f AD , f IDR are energy purchase cost, wind curtailment cost, carbon trading cost, and comprehensive demand response cost; α e , α g P is the unit electricity and gas purchase cost; e,buy (t), P g,buy (t) are the power of electricity and gas purchased in period t; δ AD P is the penalty cost for unit wind curtailment; AD (t) is the wind power abandoned during period t; P wt (t), P w,d (t) are the wind power forecast and wind power consumption in period t; δ P , δ c are the compensation coefficients of transferable and curtailable loads participating in the response, respectively; is the transferable load participating in the response during period t; is the load that can be reduced during the response period t.

[0028] As a further embodiment of the present invention, The expression of efficiency is:

[0029]

[0030] Where η ex (t) is the heat and power generation unit in period t Efficiency; P h,GT (t) is the thermal power generated by the gas turbine during period t; P ORC,e (t) is the electric power generated by the organic Rankine cycle during period t; P g,GT (t) is the natural gas power required by the gas turbine.

[0031] The beneficial effects of the present invention are:

[0032] (1) After adding the organic Rankine cycle device, the electricity generated by it is supplied to the power-to-gas device, realizing the coupling between the three types of energy: heat, electricity and gas. The VPP scheduling strategy of the present invention takes carbon trading into consideration, strengthens the correlation between VPP and the carbon market, further releases the guiding potential of carbon trading on VPP emission reduction, promotes the absorption of greenhouse gases by the power-to-gas device, increases the power generation of the organic Rankine cycle, reduces the carbon cost and energy purchase cost, and achieves the effect of taking into account both economic benefits and environmental benefits.

[0033] (2) After using the organic Rankine cycle to convert low-quality waste heat into electrical energy, the thermal energy of the VPP The efficiency is improved, and after the electricity generated by the organic Rankine cycle is supplied to the power-to-gas device, the energy consumption required for the electricity-to-gas conversion is increased. Compared with the dispatching strategy of decoupling the "heat-to-electricity" scheduling strategy using the organic Rankine cycle, the carbon consumption has increased. Efficiency is positively correlated with environmental benefits, which optimizes the low-carbon economic dispatch environment of virtual power plants;

[0034] (3) The present invention optimizes VPP with integrated demand response (IDR), taps into the flexible and low-carbon operation potential of the load side of VPP, promotes wind power consumption, reduces VPP's energy purchase cost and wind curtailment cost, and has a positive impact on VPP carbon emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flowchart of the present invention;

[0036] Figure 2 It is the energy cycle diagram of Virtual Power Plant VPP;

[0037] Figure 3 Predict output curves for electricity, heat loads and wind and solar units;

[0038] Figure 4 This is a diagram of the power load optimization result under Case 5 provided according to an embodiment of the present invention;

[0039] Figure 5 This is a diagram of heat load optimization results for Case 5 provided according to an embodiment of the present invention;

[0040] Figure 6 This is a gas load optimization result diagram of Case 5 provided according to an embodiment of the present invention;

[0041] Figure 7 A greenhouse gas consumption diagram for Case 5 provided according to an embodiment of the present invention;

[0042] Figure 8 For cases 1 to 5 provided according to embodiments of the present invention Efficiency graph;

[0043] Fig. 9 This is a diagram of the power load optimization result under Case 4 provided according to an embodiment of the present invention;

[0044] Fig.10 This is a heat load optimization result diagram of Case 4 provided according to an embodiment of the present invention;

[0045] Fig.11 A diagram showing the gas load optimization results of Case 4 provided according to an embodiment of the present invention;

[0046] Fig.12 This is a greenhouse gas consumption diagram for Case 4 provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other arbitrarily without conflict.

[0048] Example 1: Figure 1-12 As shown, according to the first aspect of an embodiment of the present invention, a low-carbon optimization scheduling method for cascade utilization of energy in a virtual power plant considering an organic Rankine cycle is provided, comprising: step S1, establishing a virtual power plant architecture considering an organic Rankine cycle; the virtual power plant architecture considering an organic Rankine cycle comprises a power supply side, a load side, and an energy storage side, the power supply side comprises wind power and a combined heat and power unit, and the combined heat and power unit combines an organic Rankine cycle, a power-to-gas unit, a gas turbine, and a waste heat boiler, the load side comprises three types of loads: electricity, heat, and gas, and the energy storage side comprises three types of energy storage devices: electricity, heat, and gas; step S2, a virtual power plant architecture based on an organic Rankine cycle, in which thermal energy utilization is considered After calculating the efficiency, an organic Rankine cycle output model for power generation using waste heat is established; a power-to-gas operation model is established; the organic Rankine cycle output model and the power-to-gas operation model are combined to establish an output model of a combined heat and power unit including power-to-gas and organic Rankine cycle devices; step S3, under the carbon quota mechanism, a step-by-step carbon trading model is established; step S4, a comprehensive demand response model is established; step S5, based on the step-by-step carbon trading model and the comprehensive demand response model, an objective function and constraints for minimizing the comprehensive operating cost of a virtual power plant considering an organic Rankine cycle are established; based on the objective function and constraints for minimizing the comprehensive operating cost of a virtual power plant considering an organic Rankine cycle, a low-carbon optimal scheduling of energy cascade utilization of a virtual power plant considering an organic Rankine cycle is achieved.

[0049] Furthermore, the output model of the combined heat and power unit containing power-to-gas and organic Rankine cycle device is expressed as:

[0050]

[0051] P P2G,g (t) = η P2G P P2G,e (t) (4)

[0052] P P2G,e(t) = P ORC,e (t)+P a,w (t) (5)

[0053]

[0054] Where P ORC,h (t), P WHB,h (t) are the heat power of the organic Rankine cycle and the heat power entering the waste heat boiler during period t; P ORC,e (t) is the electric power generated by the organic Rankine cycle during period t; η ORC is the organic Rankine cycle thermoelectric conversion efficiency; P h,WHB (t) is the heating power of the waste heat boiler during period t; η WHB is the heat loss efficiency; P e,GT (t), P h,GT (t) are the electrical power and thermal power generated by the gas turbine during period t; P g,GT (t) is the natural gas power required by the gas turbine during period t; η e , η h,GT are the gas-to-electricity and gas-to-heat conversion efficiencies of the gas turbine during period t, respectively; are the upper and lower limits of GT gas power respectively; P h,GB (t) is the thermal power generated by the gas boiler during period t, P g,GB (t) is the gas power required by the gas boiler during period t; η GB is the heat conversion efficiency of the gas boiler; are the upper and lower limits of gas power of gas boiler respectively; P P2G,g (t) is the natural gas power output of the power-to-gas device during period t; η P2G is the conversion efficiency of the power-to-gas device; P P2G,e (t) is the electric power required by the power-to-gas device during period t; P a,w (t) is the wind power abandoned during period t; is the greenhouse gas mass of synthetic natural gas during period t; In the above formula, formula (1) is the organic Rankine cycle output model, and formula (4)-(6) are the power-to-gas operation models.

[0055] Furthermore, the step S3 comprises:

[0056] S3.1: Under the carbon trading mechanism, in order to reduce carbon emissions from the operation of virtual power plants, the amount of greenhouse gases emitted on both the source and load sides is measured. The model is:

[0057] D VPP =D e,buy +D GB +D GT +D g,load (7)

[0058]

[0059] Where D VPP , D e,buy , D GB , D GT , D g,load are the carbon quotas for VPP, purchased electricity, gas boilers, gas turbines and gas loads; e,buy , χ h , χ g , χ e-h are the carbon quota and thermal power conversion coefficient per unit electric power, unit thermal power and unit gas load respectively; P e,buy (t) is the purchased power in period t; P h,GB (t) is the thermal power generated by the gas boiler in period t; P e,GT (t), P h,GT (t) are respectively the electric power and thermal power generated by the gas turbine in period t, T is the scheduling period, and the present invention takes 24; P g,load (t) is the gas load during period t.

[0060] S3.2: The actual carbon emission model is:

[0061] D VPP,a =D e,buy,a +D g,load,a +D IE,a -D P2G,a (9)

[0062]

[0063] D a =D VPP,a -D VPP (11)

[0064] Where D VPP,a , D e,buy,a , D g,load,a are the actual carbon emissions of VPP, purchased electricity, and gas load, respectively. IE,a is the sum of the actual carbon emissions of gas turbines and gas boilers, D P2G,a Carbon emissions absorbed by the power-to-gas device; P IE,a (t) is the equivalent output power of the combined heat and power unit and the gas boiler during period t; x1, y1, z1 are the carbon emission coefficients of the coal-fired unit, and x2, y2, z2 are the carbon emission coefficients of natural gas combustion; ξ, are the equivalent carbon emission parameters of gas load and the absorption parameters of power-to-gas device respectively; P g,load (t) is the gas load during period t; P e,GT(t) is the electric power generated by the gas turbine during period t; P h,GT (t) is the thermal power generated by the gas turbine during period t; P h,GB (t) is the thermal power generated by the gas boiler during period t; P P2G,g (t) is the natural gas power output of the power-to-gas device during period t; D a Carbon emissions from virtual power plants participating in carbon trading.

[0065] S3.3: The tiered carbon trading model is:

[0066]

[0067] In the formula, is the carbon trading cost; λ is the carbon trading base price; L is the length of the carbon emission interval; α is the price increase.

[0068] Furthermore, the step S4 comprises:

[0069] A comprehensive demand response model on the load side is established to improve the acceptance capacity of wind power. The comprehensive demand response model is:

[0070]

[0071] Where P k,load (t) is the value of the kth load in the t period, and in the present invention, k is 3 (i.e., electricity, heat, and gas loads); is the rigid load of the kth load in period t; is the load that can be reduced for the kth load in period t; is the transferable load of the kth load in period t.

[0072] Furthermore, the step S5 comprises:

[0073] Solve the minimum comprehensive operating cost of the virtual power plant, optimize it with the minimum comprehensive operating cost as the goal, and build a low-carbon economic dispatch model of the virtual power plant considering the organic Rankine cycle:

[0074]

[0075] Where F is the total cost of the virtual power plant; buy 、f AD , f IDR are energy purchase cost, wind curtailment cost, carbon trading cost, and comprehensive demand response cost; α e , α g P is the unit electricity and gas purchase cost; e,buy (t), P g,buy (t) are the power of electricity and gas purchased in period t; δ ADP is the penalty cost for unit wind curtailment; AD (t) is the wind power abandoned during period t; P wt (t), P w,d (t) are the wind power forecast and wind power consumption in period t; δ P , δ c are the compensation coefficients of transferable and curtailable loads participating in the response, respectively; is the transferable load participating in the response during period t; is the load that can be reduced during the response period t.

[0076] The constraints are as follows:

[0077] Power balance constraints:

[0078]

[0079] P h,WHB (t)+P h,GT (t) = P h,load (t)+P ES,h (t)(19)

[0080]

[0081] Said The expression of efficiency is:

[0082]

[0083] Where P e,buy (t) is the purchased power in period t; P e,GT (t) is the electric power generated by the gas turbine during period t; P ORC,e (t) is the electric power generated by the organic Rankine cycle during period t; P w,d (t) is the wind power consumption power in period t; P P2G,e (t) is the electric power required by the power-to-gas device during period t; P e,load (t) is the electrical load during period t; P ES,e (t) is the output power of the electric energy storage during the period t; is the maximum power purchase; P h,WHB (t) is the heating power of the waste heat boiler in period t; P h,GT (t) is the thermal power generated by the gas turbine during period t; P h,load (t) is the heat load during period t; P ES,h (t) is the release power of the heat storage tank; P g,buy (t) is the gas purchasing power in period t; P P2G,g (t) is the natural gas power output of the power-to-gas device during period t; P g,load (t) is the gas load during period t; PES,g (t) is the output power of the gas tank; P g,GT (t) is the natural gas power required by the gas turbine; P g,GB (t) is the gas power required by the gas boiler; is the maximum gas purchasing power; are the charging and discharging powers of the nth type of energy storage respectively; is the maximum charge and discharge power of the nth type of energy storage; is the charging efficiency and discharging efficiency of the nth energy storage; P ES,n (t) is the output power of the nth energy storage during period t; S n (t) is the energy storage capacity during period t; is the maximum and minimum capacity of the nth type of energy storage; is the rated capacity of the nth type of energy storage; n is the energy of electricity, heat and gas, and is taken as 3 in the present invention; η ex (t) is the heat and power generation unit in period t efficiency.

[0084] According to a second aspect of an embodiment of the present invention, a low-carbon optimization scheduling system for energy cascade utilization of a virtual power plant considering an organic Rankine cycle is provided, comprising: a first establishment module for establishing a virtual power plant architecture considering an organic Rankine cycle; a second establishment module for establishing a virtual power plant architecture based on an organic Rankine cycle, in consideration of thermal energy utilization After calculating the efficiency, an organic Rankine cycle output model for power generation using waste heat is established; a power-to-gas operation model is established; the organic Rankine cycle output model and the power-to-gas operation model are combined to establish an output model of a combined heat and power unit containing power-to-gas and organic Rankine cycle devices; a third establishment module is used to establish a step-by-step carbon trading model under the carbon quota mechanism; a fourth establishment module is used to establish a comprehensive demand response model; an optimization scheduling module is used to establish an objective function and constraints for minimizing the comprehensive operating cost of a virtual power plant considering an organic Rankine cycle based on the step-by-step carbon trading model and the comprehensive demand response model; based on the objective function and constraints for minimizing the comprehensive operating cost of a virtual power plant considering an organic Rankine cycle, a low-carbon optimized scheduling of energy cascade utilization of a virtual power plant considering an organic Rankine cycle is achieved.

[0085] Furthermore, in order to analyze the impact of the proposed model on the carbon emissions and economic benefits of virtual power plants, the present invention sets up 5 cases for comparative analysis, namely:

[0086] Case 1: No organic Rankine cycle device is installed and the purchased electricity comes from coal-fired units. The load side of the virtual power plant is optimized by comprehensive demand response;

[0087] Case 2: Without taking into account the organic Rankine cycle, the load side of the virtual power plant is optimized with integrated demand response;

[0088] Case 3: Based on Case 2, the organic Rankine cycle is taken into account to decouple the "heat-to-electricity" mode, that is, the electricity generated by the organic Rankine cycle is directly supplied to the electrical load, and the VPP load side is optimized by comprehensive demand response;

[0089] Case 4: Considering the organic Rankine cycle, for Efficiency is coupled with low-carbon scheduling, i.e. the electricity generated by the organic Rankine cycle is supplied to the power-to-gas device; the VPP load side is optimized with heat demand response;

[0090] Case 5: Considering the Organic Rankine Cycle (ORC) for Efficiency is coupled with low-carbon scheduling, that is, the electricity generated by the organic Rankine cycle is supplied to the power-to-gas device; the VPP load side is optimized with comprehensive demand response.

[0091] According to the above five cases, the dispatch results of virtual power plants are analyzed.

[0092] In order to verify the effectiveness and applicability of the proposed model, this paper takes the virtual power plant as the research object, takes 24 hours as the cycle, 1 hour as the step length, and takes the minimum comprehensive operating cost as the goal. The MATLAB2018b simulation software is used to call the Gurobi solver for solution. The virtual power plant equipment parameters are shown in Table 1, the three types of energy storage capacity and the upper and lower limits of the storage capacity are shown in Table 2, and the system electricity, heat, gas load and wind power forecast output are shown in Table 2. Figure 3 As shown in the figure; Carbon quota of coal-fired units that purchase electricity from outside e,buy is 0.798kg / kWh, and the carbon quota for burning natural gas is h is 0.385kg / kWh; the equivalent carbon emission parameter of gas load is 0.18 kg / kWh, the carbon trading base price λ is determined to be 0.25 yuan / kilogram (yuan / kg), and the carbon emission interval length is 2000 kilograms (kg). In addition, it should be pointed out that the unit wind abandonment penalty cost δ AD It is set to 0.1 yuan / kWh. The operating costs of virtual power plants under different cases are shown in Table 3.

[0093] Table 1

[0094] Virtual power plant equipment Power lower and upper limits (kW) Conversion efficiency / % P2G 0、500 60 GT 0、1000 22 (gas to electricity), 72 (gas to heat) ORC 0、600 80 WHB 0、600 80 GB 0、800 80

[0095] In Table 1, P2G is a power-to-gas device; GT is a gas turbine, which is a power generation device in a combined heat and power unit; ORC is an organic Rankine cycle device; WHB is a waste heat boiler, which is a device in a combined heat and power unit that collects heat to supply heat load; GB is a gas boiler, which is a device in a virtual power plant that directly burns natural gas and collects heat to supply heat load.

[0096] Table 2

[0097] type Capacity(kWh) Storage lower / upper limit Electric energy storage 450 10％ / 90％ Heat storage tank 500 10％ / 90％ gas tank 300 10％ / 90％

[0098] Table 3

[0099]

[0100] From the running results in Table 3 and Figure 4-Figure 12 The specific situation is as follows:

[0101] From the operation of Case 1, it can be seen that since the purchased electricity is from coal-fired units and there is no organic Rankine cycle device, the purchased electricity is the largest, the carbon trading cost and the energy purchase cost are the largest, and the carbon consumption is the smallest.

[0102] From the operation of Case 2, it can be seen that when ORC is not taken into account, only GT electric power and abandoned wind power are supplied to P2G, and the amount of greenhouse gas consumed by P2G is limited, which is 1852.3 kg. In the total cost, carbon trading costs and energy purchase costs account for 36.7% and 61.7% of the total cost respectively.

[0103] From the operation of Case 3, it can be seen that after taking ORC into account and directly supplying it to the load to decouple the "heat-to-electricity" mode, the daily carbon consumption is approximately 2398.7 kg. Compared with Case 2, the carbon trading cost is reduced by approximately 2.3% and the total cost is reduced by approximately 5.9%.

[0104] From the operation of Case 4, it can be seen that after taking ORC into account, when the supply and demand balance is achieved by heat demand response, the total cost, energy purchase cost, and carbon trading cost are 35,181.9 yuan, 20,756.7 yuan, and 14,355.4 yuan respectively, and the total carbon consumption on the dispatch day is 3,328.6 kg.

[0105] From the operation of Case 5, it can be seen that after considering ORC and achieving supply and demand balance with comprehensive demand response, the low-quality thermal energy in the cogeneration CHP is effectively utilized. After ORC is coupled with P2G, compared with Case 2, the energy purchase cost is reduced by about 10.7%, and the total carbon consumption per day is 3646.8kg, while CHP Efficiency is positively correlated with the greenhouse gas consumption of synthetic natural gas (greenhouse gas consumption is carbon consumption).

[0106] In terms of cost and environmental benefits, when ORC is not taken into account, the total system cost and carbon trading cost are the highest in Cases 1 and 2. After ORC is taken into account in Case 3, the “heat-to-electricity” model of CHP is decoupled, which improves While increasing efficiency, it also increases CHP power generation and reduces energy purchase costs. The carbon consumption on the dispatch day is 2398.7 kg higher than that in Cases 1 and 2. Case 4 uses ORC to achieve Efficiency is coupled with low-carbon scheduling, but when supply and demand balance is achieved only by heat demand response, the carbon consumption on the scheduling day is 3328.6 kg; when Case 5 achieves supply and demand balance by comprehensive demand response for electricity, heat and gas, although the total cost and energy purchase cost are slightly higher than Case 4, the carbon consumption increases compared with Case 4, which is 3646.8 kg. The carbon trading cost is also relatively small, and the environmental benefits are better than Case 4. The low-carbon potential of comprehensive demand response is higher than that of single demand response.

[0107] In terms of energy efficiency, VPP Efficiency can be as Figure 8 As shown, Cases 1 and 2 do not use ORC to generate electricity, so their thermal energy The lowest efficiency; Case 3 is to use ORC to decouple “heat to electricity”, which is not highly correlated with environmental benefits. The efficiency is also low, and the greenhouse gas consumption on the dispatch day is also small; while cases 4 and 5 are Efficiency is coupled with low-carbon operation. Under the guidance of carbon trading, the daily carbon consumption of dispatch is greater than that of Case 3. The efficiency is positively correlated with the environmental benefits. Efficiency is coupled with low-carbon operation, and virtual power plants are optimized under the guidance of carbon trading and heat demand response. Although the energy purchase cost of Case 4 is slightly lower than that of Case 5, the carbon consumption is significantly reduced compared with Case 5, and the environmental benefit is slightly less than that of Case 5. Figure 9-11 This is the power balance diagram of electricity, heat and gas for Case 4. Fig.12 is the dispatching daily carbon consumption of Case 4; Case 5 is Efficiency is coupled with low-carbon operation. Under the guidance of carbon trading and comprehensive demand response, the daily carbon consumption of dispatch is greater than that of Case 3. Figure 7 and Figure 8 It can be seen that The size of efficiency is positively correlated with environmental benefits. Figure 4 , Figure 5 , Figure 6 This is the power balance diagram of the virtual power plant in Case 5. After meeting the daily supply and demand balance of the virtual power plant, the present invention has greatly improved the economic efficiency and carbon emission control level of the virtual power plant. By applying the above technical solution, it can be seen that the method proposed in the present invention improves the economic efficiency and carbon emission level of the virtual power plant while improving the energy utilization efficiency of the virtual power plant.

[0108] The sensitivity analysis of VPP to carbon trading in each case is shown in Tables 4 to 8. Under different carbon trading base prices, VPP has different sensitivities to carbon trading. From the simulation results, it can be seen that in each case, as the carbon trading base price rises, the carbon trading cost increases, but the carbon consumption decreases. The deeper the correlation with carbon trading, the more the carbon consumption decreases.

[0109] Table 4 Case 1 Carbon Trading Sensitivity Analysis

[0110] Carbon trading base price / (yuan / kg) Total cost / yuan Carbon trading cost / yuan Carbon consumption / kg 0.25 38441.6 14844.8 1552.3 0.3 43360.4 17948.5 1539.1 0.35 45463.2 20628.9 1535.5

[0111] Table 5 Case 2 Carbon Trading Sensitivity Analysis

[0112] Carbon trading base price / (yuan / kg) Total cost / yuan Carbon trading cost / yuan Carbon consumption / kg 0.25 39595.6 14530.2 1852.3 0.3 42490.4 17348.5 1839.1 0.35 45381.2 20228.9 1835.5

[0113] Table 6 Case 3 Carbon Trading Sensitivity Analysis

[0114] Carbon trading base price / (yuan / kg) Total cost / yuan Carbon trading cost / yuan Carbon consumption / kg 0.25 40203.2 16614.0 2398.7 0.3 42490.4 17348.5 2316.9 0.35 42946.6 18981.1 2251.4

[0115] Table 7 Case 4 Carbon Trading Sensitivity Analysis

[0116] Carbon trading base price / (yuan / kg) Total cost / yuan Carbon trading cost / yuan Carbon consumption / kg 0.25 35181.9 14355.4 3328.6 0.3 38052.5 17191.3 3303.1 0.35 40909.7 19910.8 3211.0

[0117] Table 8 Case 5 Carbon Trading Sensitivity Analysis

[0118] Carbon trading base price / (yuan / kg) Total cost / yuan Carbon trading cost / yuan Carbon consumption / kg 0.25 35821.8 14177.5 3646.8 0.3 38655.3 16972.2 3610.4 0.35 41451.8 19419.4 3309.3

[0119] It can be seen from Tables 4 to 8 that under different carbon trading base prices, the carbon reduction guidance capacity of carbon trading on VPP is different. Setting reasonable carbon trading base price parameters can maximize the release of its low-carbon guidance potential for VPP.

[0120] The present invention draws the following conclusions:

[0121] (1) Considering the VPP scheduling strategy after carbon trading, the correlation between VPP and carbon market is strengthened, the guiding potential of carbon trading on VPP emission reduction is further released, the absorption of greenhouse gases by P2G is promoted, and the power generation of ORC is increased. Compared with Case 1, the carbon trading cost of Case 5 is reduced by about 667.3 yuan, and the total cost is reduced by about 2620.6 yuan, taking into account both economic and environmental benefits.

[0122] (2) After using ORC to convert low-quality waste heat into electricity, VPP heat energy The efficiency is improved. After the electricity generated by ORC is supplied to P2G, the energy consumption required for electricity-gas conversion is increased. Compared with the dispatching strategy of "heat-based electricity" using ORC decoupling in Case 3, the carbon consumption in Case 5 is increased by 1248.1kg. Efficiency is positively correlated with environmental benefits, which optimizes the low-carbon economic dispatch environment of VPP.

[0123] (3) Considering the scheduling strategy of VPP electricity, heat and gas energy coupling, the advantages of energy complementarity are effectively brought into play. Under the condition of roughly the same total cost, the carbon consumption of Case 5 on the scheduling day is about 318 kg higher than that of Case 4, and the environmental benefit is more obvious, that is, the low-carbon nature of the comprehensive demand response is higher than that of the single demand response.

[0124] (4) Under different base prices, the carbon trading’s ability to guide VPPs to reduce carbon emissions varies. Setting reasonable carbon trading base price parameters can maximize its low-carbon guidance potential for VPPs.

[0125] Reference significance: ORC is a device that uses low-temperature waste heat to generate electricity. The different circulating working fluids and circulating conditions will affect the conversion efficiency. The establishment of the model and the implementation of the strategy in this invention will provide a reference for the subsequent ORC device to convert energy under different circulating working fluids and working conditions. The research on the coupling of efficiency and low-carbon scheduling and the analysis of VPP's sensitivity to carbon trading under different carbon trading parameters provide theoretical support.

[0126] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A low-carbon optimization scheduling method for energy cascade utilization of virtual power plants considering organic Rankine cycle, characterized in that: include: Step S1, establishing a virtual power plant architecture considering the organic Rankine cycle; the virtual power plant architecture considering the organic Rankine cycle includes a power supply side, a load side, and an energy storage side. The power supply side includes wind power and cogeneration units, and the cogeneration unit combines the organic Rankine cycle, power-to-gas, gas turbine, and waste heat boiler. The load side includes three types of loads: electricity, heat, and gas. The energy storage side includes three types of energy storage devices: electricity, heat, and gas. Step S2: Virtual power plant architecture based on organic Rankine cycle, considering the utilization of thermal energy After the efficiency is calculated, an organic Rankine cycle output model for power generation using waste heat is established; a power-to-gas operation model is established; the organic Rankine cycle output model and the power-to-gas operation model are combined to establish an output model for a combined heat and power unit containing a power-to-gas and organic Rankine cycle device; Step S3: Establish a stepped carbon trading model under the carbon quota mechanism; Step S4: establishing a comprehensive demand response model; Step S5: Based on the stepped carbon trading model and the comprehensive demand response model, establish the objective function and constraints for minimizing the comprehensive operating cost of the virtual power plant considering the organic Rankine cycle; based on the objective function and constraints for minimizing the comprehensive operating cost of the virtual power plant considering the organic Rankine cycle, realize the low-carbon optimal scheduling of the virtual power plant energy cascade utilization considering the organic Rankine cycle.

2. The low-carbon optimization scheduling method for energy cascade utilization of virtual power plants considering organic Rankine cycle according to claim 1 is characterized in that: The output model of the combined heat and power unit containing power-to-gas and organic Rankine cycle device is expressed as: P P2G,g (t)=η P2G P P2G,e (t); P P2G,e (t)=P ORC,e (t)+P a,w (t); Where P ORC,h (t), P WHB,h (t) are the heat power of the organic Rankine cycle and the heat power entering the waste heat boiler during period t; P ORC,e (t) is the electrical power generated by the organic Rankine cycle during period t; η ORC is the organic Rankine cycle thermoelectric conversion efficiency; P h,WHB (t) is the heating power of the waste heat boiler during period t; η WHB is the heat loss efficiency; P e,GT (t), P h,GT (t) are the electrical power and thermal power generated by the gas turbine during period t; P g,GT (t) is the natural gas power required by the gas turbine during period t; η e , η h,GT are the gas-to-electricity and gas-to-heat conversion efficiencies of the gas turbine during period t, respectively; are the upper and lower limits of GT gas power respectively; P h,GB (t) is the thermal power generated by the gas boiler during period t, P g,GB (t) is the gas power required by the gas boiler during period t; η GB is the heat conversion efficiency of the gas boiler; are the upper and lower limits of gas power of gas boiler respectively; P P2G,g (t) is the natural gas power output of the power-to-gas device during period t; η P2G is the conversion efficiency of the power-to-gas device; P P2G,e (t) is the electric power required by the power-to-gas device during period t; P a,w (t) is the wind power abandoned during period t; is the greenhouse gas mass of synthetic natural gas during period t; For transformation efficiency.

3. The low-carbon optimization scheduling method for energy cascade utilization of virtual power plants considering organic Rankine cycle according to claim 1 is characterized in that: The step S3 comprises: Obtain virtual power plant carbon quotas based on the virtual power plant carbon quota model; According to the actual carbon emission model of the virtual power plant, the actual carbon emission of the virtual power plant is obtained; Obtain the carbon emissions of virtual power plants participating in carbon trading based on the carbon quotas of virtual power plants and actual carbon emissions of virtual power plants; Based on the carbon emissions of virtual power plants participating in carbon trading, a stepped carbon trading model is established to obtain the carbon trading costs.

4. The low-carbon optimization scheduling method for cascade utilization of energy in a virtual power plant considering an organic Rankine cycle according to claim 3 is characterized in that: The actual carbon emission model of the virtual power plant is: D VPP,a =D e,buy,a +D g,load,a +D IE,a -D P2G,a ; Where D VPP,a , D e,buy,a , D g,load,a are the actual carbon emissions of virtual power plants, purchased electricity, and gas loads, respectively. IE,a is the sum of the actual carbon emissions of gas turbines and gas boilers, D P2G,a Carbon emissions absorbed by the power-to-gas device.

5. The low-carbon optimization scheduling method for energy cascade utilization of virtual power plants considering organic Rankine cycle according to claim 3 is characterized in that: The tiered carbon trading model is: D a =D VPP,a -D VPP ; In the formula, f CO2 is the carbon trading cost; λ is the carbon trading base price; D a is the carbon emissions of the virtual power plant participating in carbon trading; L is the length of the carbon emission interval; α is the price increase; D VPP,a is the actual carbon emission of the virtual power plant; D VPP Carbon quota for virtual power plants.

6. The low-carbon optimization scheduling method for energy cascade utilization of virtual power plants considering organic Rankine cycle according to claim 1 is characterized in that: The step S5 comprises: Taking power balance constraint as constraint condition and minimizing comprehensive operation cost as goal for optimization, the low-carbon economic dispatch model of virtual power plant considering organic Rankine cycle is constructed as follows: Where F is the total cost of the virtual power plant; f buy 、f AD , f IDR are energy purchase cost, wind curtailment cost, carbon trading cost, and comprehensive demand response cost; α e , α g P is the unit electricity and gas purchase cost; e,buy (t), P g,buy (t) are the power of electricity and gas purchased in period t; δ AD P is the penalty cost for unit wind curtailment; AD (t) is the wind power abandoned during period t; P wt (t), P w,d (t) are the wind power forecast and wind power consumption in period t; δ P , δ c are the compensation coefficients of transferable and curtailable loads participating in the response, respectively; is the transferable load participating in the response during period t; is the load that can be reduced during the response period t.

7. The low-carbon optimization scheduling method for energy cascade utilization of virtual power plants considering organic Rankine cycle according to claim 1 is characterized in that: Said The expression of efficiency is: Where η ex (t) is the heat and power generation unit in period t Efficiency; P h,GT (t) is the thermal power generated by the gas turbine during period t; P ORC,e (t) is the electric power generated by the organic Rankine cycle during period t; P g,GT (t) is the natural gas power required by the gas turbine.

Images